Airborne laserscanning (or lidar) has become a very important technique for the acquisition of digital terrain model data. Beyond this, the technique is increasingly being used for the acquisition of point clouds for 3D modeling of a wide range of objects, such as buildings, vegetation, or electrical power lines. As an active technique, airborne laserscanning offers a high reliability even over terrain with poor image contrast. The precision of the technique is often specified to be on the order of one to two decimeters. By reason of its primary use in digital terrain modeling, examinations of the precision potential of airborne laserscanning have so far been concentrated on the height precision. With the use of the technique for general 3D reconstruction tasks and the increasing resolution of laserscanner systems, the planimetric precision of laserscanner point clouds becomes an important issue. In addition to errors in the laser distance meter and the deflecting mirror system, the error budget of airborne laserscanning instruments is strongly influenced by the GPS/INS systems used for sensor pose (position and orientation) determination. Errors of these systems often lead to the deformation of laserscanner data strips and may become evident as discrepancies in the overlap region between neighboring strips in a block of laserscanner data. The paper presents least-squares matching implemented on a TIN structure as a general tool for the determination of laserscanner strip discrepancies in all three coordinate directions, using both height and reflectance data. Practical problems of applying matching techniques to 2.5D laserscanner point clouds are discussed and solved, and the success of the technique is shown on the basis of several datasets. Applying least-squares matching techniques to dense laserscanner data in a TIN structure, strip discrepancies can be determined with centimeter precision for the height coordinate and decimeter precision for the planimetric coordinates.